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@@ -7,6 +7,8 @@ Combining Noise-Conditioned Perception with DPO significantly outperforms baseli
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  We publish LoRA weights that are trained for 10 H100 GPU hours on a small subset of a Pick-a-Picv2 dataset. We removed all non-absolute winners for each prompt and our final prompts and image ids can be found [here](https://drive.google.com/file/d/1q1fvItyLq2YI_O6oNLyNYiB9opeZLYdB/view?usp=sharing)
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  To try our LoRA weights and compare with a baseline:
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  ```python
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  from diffusers import DiffusionPipeline
 
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  We publish LoRA weights that are trained for 10 H100 GPU hours on a small subset of a Pick-a-Picv2 dataset. We removed all non-absolute winners for each prompt and our final prompts and image ids can be found [here](https://drive.google.com/file/d/1q1fvItyLq2YI_O6oNLyNYiB9opeZLYdB/view?usp=sharing)
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+ training code: https://github.com/sakharok13/Aligning-Stable-Diffusion-with-Noise-Conditioned-Perception
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  To try our LoRA weights and compare with a baseline:
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  ```python
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  from diffusers import DiffusionPipeline